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You searched for +publisher:"University of Colorado" +contributor:("Alireza Doostan"). Showing records 1 – 30 of 41 total matches.

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University of Colorado

1. Dunham, Benjamin Zane. High-Order Automatic Differentiation of Unmodified Linear Algebra Routines via Nilpotent Matrices.

Degree: PhD, 2017, University of Colorado

  This work presents a new automatic differentiation method, Nilpotent Matrix Differentiation (NMD), capable of propagating any order of mixed or univariate derivative through common… (more)

Subjects/Keywords: adjoint; automatic differentiation; complex step; hessian-vector; linear algebra; nilpotent element; Aerospace Engineering; Applied Mathematics; Mathematics

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APA (6th Edition):

Dunham, B. Z. (2017). High-Order Automatic Differentiation of Unmodified Linear Algebra Routines via Nilpotent Matrices. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/228

Chicago Manual of Style (16th Edition):

Dunham, Benjamin Zane. “High-Order Automatic Differentiation of Unmodified Linear Algebra Routines via Nilpotent Matrices.” 2017. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/228.

MLA Handbook (7th Edition):

Dunham, Benjamin Zane. “High-Order Automatic Differentiation of Unmodified Linear Algebra Routines via Nilpotent Matrices.” 2017. Web. 01 Mar 2021.

Vancouver:

Dunham BZ. High-Order Automatic Differentiation of Unmodified Linear Algebra Routines via Nilpotent Matrices. [Internet] [Doctoral dissertation]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/228.

Council of Science Editors:

Dunham BZ. High-Order Automatic Differentiation of Unmodified Linear Algebra Routines via Nilpotent Matrices. [Doctoral Dissertation]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/asen_gradetds/228


University of Colorado

2. Farr, Michaela, Ms. Bifidelity Methods for Polynomial Chaos Expansions.

Degree: MS, 2017, University of Colorado

 This thesis provides an in-depth evaluation of two multi fidelity uncertainty quantification techniques, highlighting the key characteristics, benefits, and shortcomings therein. Physics based simulations subject… (more)

Subjects/Keywords: compressive sensing; multi fidelity methods; polynomial chaos; reduced order models; uncertainty quantification; Mathematics; Mechanical Engineering

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APA (6th Edition):

Farr, Michaela, M. (2017). Bifidelity Methods for Polynomial Chaos Expansions. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/mcen_gradetds/180

Chicago Manual of Style (16th Edition):

Farr, Michaela, Ms. “Bifidelity Methods for Polynomial Chaos Expansions.” 2017. Masters Thesis, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/mcen_gradetds/180.

MLA Handbook (7th Edition):

Farr, Michaela, Ms. “Bifidelity Methods for Polynomial Chaos Expansions.” 2017. Web. 01 Mar 2021.

Vancouver:

Farr, Michaela M. Bifidelity Methods for Polynomial Chaos Expansions. [Internet] [Masters thesis]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/mcen_gradetds/180.

Council of Science Editors:

Farr, Michaela M. Bifidelity Methods for Polynomial Chaos Expansions. [Masters Thesis]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/mcen_gradetds/180


University of Colorado

3. Balducci, Marc. Orbit Uncertainty Propagation with Separated Representations.

Degree: PhD, 2018, University of Colorado

 In light of recent collisions and an increasing population of objects in Earth orbit, the space situational awareness community has significant motivation to develop novel… (more)

Subjects/Keywords: separated representations; uncertainty quantification; earth orbit; avoidance maneuver; multi-element algorithm; Aerospace Engineering; Mathematics

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APA (6th Edition):

Balducci, M. (2018). Orbit Uncertainty Propagation with Separated Representations. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/236

Chicago Manual of Style (16th Edition):

Balducci, Marc. “Orbit Uncertainty Propagation with Separated Representations.” 2018. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/236.

MLA Handbook (7th Edition):

Balducci, Marc. “Orbit Uncertainty Propagation with Separated Representations.” 2018. Web. 01 Mar 2021.

Vancouver:

Balducci M. Orbit Uncertainty Propagation with Separated Representations. [Internet] [Doctoral dissertation]. University of Colorado; 2018. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/236.

Council of Science Editors:

Balducci M. Orbit Uncertainty Propagation with Separated Representations. [Doctoral Dissertation]. University of Colorado; 2018. Available from: https://scholar.colorado.edu/asen_gradetds/236


University of Colorado

4. O'Neill, Nathanial James. Standard and Inception-Based Encoder-Decoder Neural Networks for Predicting the Solution Convergence of Design Optimization Algorithms.

Degree: MS, Aerospace Engineering Sciences, 2019, University of Colorado

  The goal of this work is to investigate the ways in which the capabilities of machine learning algorithms, specifically those of neural networks, can… (more)

Subjects/Keywords: convolutional neural network; design optimization; encoder decoder; inception; neural network; topology optimization; Aerospace Engineering; Computer Sciences; Mechanical Engineering

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APA (6th Edition):

O'Neill, N. J. (2019). Standard and Inception-Based Encoder-Decoder Neural Networks for Predicting the Solution Convergence of Design Optimization Algorithms. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/247

Chicago Manual of Style (16th Edition):

O'Neill, Nathanial James. “Standard and Inception-Based Encoder-Decoder Neural Networks for Predicting the Solution Convergence of Design Optimization Algorithms.” 2019. Masters Thesis, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/247.

MLA Handbook (7th Edition):

O'Neill, Nathanial James. “Standard and Inception-Based Encoder-Decoder Neural Networks for Predicting the Solution Convergence of Design Optimization Algorithms.” 2019. Web. 01 Mar 2021.

Vancouver:

O'Neill NJ. Standard and Inception-Based Encoder-Decoder Neural Networks for Predicting the Solution Convergence of Design Optimization Algorithms. [Internet] [Masters thesis]. University of Colorado; 2019. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/247.

Council of Science Editors:

O'Neill NJ. Standard and Inception-Based Encoder-Decoder Neural Networks for Predicting the Solution Convergence of Design Optimization Algorithms. [Masters Thesis]. University of Colorado; 2019. Available from: https://scholar.colorado.edu/asen_gradetds/247


University of Colorado

5. Geiss, Markus Josef. Level-Set-XFEM-Density Topology Optimization of Active Structures: Methods and Applications.

Degree: PhD, Aerospace Engineering Sciences, 2019, University of Colorado

 To unlock the potential of advanced manufacturing technologies like additive manufacturing, an inherent need for sophisticated design tools exists. In this thesis, a systematic approach… (more)

Subjects/Keywords: 3D printing; 4D printing; active structures; level set XFEM; topology optimization; Aerospace Engineering; Applied Mechanics; Computer Sciences

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APA (6th Edition):

Geiss, M. J. (2019). Level-Set-XFEM-Density Topology Optimization of Active Structures: Methods and Applications. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/254

Chicago Manual of Style (16th Edition):

Geiss, Markus Josef. “Level-Set-XFEM-Density Topology Optimization of Active Structures: Methods and Applications.” 2019. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/254.

MLA Handbook (7th Edition):

Geiss, Markus Josef. “Level-Set-XFEM-Density Topology Optimization of Active Structures: Methods and Applications.” 2019. Web. 01 Mar 2021.

Vancouver:

Geiss MJ. Level-Set-XFEM-Density Topology Optimization of Active Structures: Methods and Applications. [Internet] [Doctoral dissertation]. University of Colorado; 2019. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/254.

Council of Science Editors:

Geiss MJ. Level-Set-XFEM-Density Topology Optimization of Active Structures: Methods and Applications. [Doctoral Dissertation]. University of Colorado; 2019. Available from: https://scholar.colorado.edu/asen_gradetds/254


University of Colorado

6. Gipe, Donald Stephen. Surrogate Modelling of Combustion Systems for Robust Optimized Scramjet Design.

Degree: MS, Aerospace Engineering Sciences, 2012, University of Colorado

  Substantial computational time to develop high speed propulsion systems is the number one challenge facing future development of thrust producing scramjets over a wide… (more)

Subjects/Keywords: Aerospace Engineering

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APA (6th Edition):

Gipe, D. S. (2012). Surrogate Modelling of Combustion Systems for Robust Optimized Scramjet Design. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/43

Chicago Manual of Style (16th Edition):

Gipe, Donald Stephen. “Surrogate Modelling of Combustion Systems for Robust Optimized Scramjet Design.” 2012. Masters Thesis, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/43.

MLA Handbook (7th Edition):

Gipe, Donald Stephen. “Surrogate Modelling of Combustion Systems for Robust Optimized Scramjet Design.” 2012. Web. 01 Mar 2021.

Vancouver:

Gipe DS. Surrogate Modelling of Combustion Systems for Robust Optimized Scramjet Design. [Internet] [Masters thesis]. University of Colorado; 2012. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/43.

Council of Science Editors:

Gipe DS. Surrogate Modelling of Combustion Systems for Robust Optimized Scramjet Design. [Masters Thesis]. University of Colorado; 2012. Available from: https://scholar.colorado.edu/asen_gradetds/43


University of Colorado

7. Balin, Riccardo. The Effects of Time Step on Reynolds Averaged Navier-Stokes Simulations of High-Lift Flows.

Degree: MS, Aerospace Engineering Sciences, 2016, University of Colorado

  The linear finite element, time-implicit PHASTA flow solver was employed to perform Reynolds Averaged Navier-Stokes (RANS) simulations of the DLR F11 model studied for… (more)

Subjects/Keywords: Computational Fluid Dynamics; High Lift; RANS; Time Step; Aerodynamics and Fluid Mechanics

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APA (6th Edition):

Balin, R. (2016). The Effects of Time Step on Reynolds Averaged Navier-Stokes Simulations of High-Lift Flows. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/136

Chicago Manual of Style (16th Edition):

Balin, Riccardo. “The Effects of Time Step on Reynolds Averaged Navier-Stokes Simulations of High-Lift Flows.” 2016. Masters Thesis, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/136.

MLA Handbook (7th Edition):

Balin, Riccardo. “The Effects of Time Step on Reynolds Averaged Navier-Stokes Simulations of High-Lift Flows.” 2016. Web. 01 Mar 2021.

Vancouver:

Balin R. The Effects of Time Step on Reynolds Averaged Navier-Stokes Simulations of High-Lift Flows. [Internet] [Masters thesis]. University of Colorado; 2016. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/136.

Council of Science Editors:

Balin R. The Effects of Time Step on Reynolds Averaged Navier-Stokes Simulations of High-Lift Flows. [Masters Thesis]. University of Colorado; 2016. Available from: https://scholar.colorado.edu/asen_gradetds/136


University of Colorado

8. Farr, Michaela. Bifidelity Methods for Polynomial Chaos Expansions.

Degree: MS, Mechanical Engineering, 2017, University of Colorado

 This thesis provides an in-depth evaluation of two multi fidelity uncertainty quantification techniques, highlighting the key characteristics, benefits, and shortcomings therein. Physics based simulations subject… (more)

Subjects/Keywords: Compressive Sensing; Multi fidelity Methods; Polynomial Chaos; Reduced Order Models; Uncertainty Quantification; Mathematics

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APA (6th Edition):

Farr, M. (2017). Bifidelity Methods for Polynomial Chaos Expansions. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/mcen_gradetds/144

Chicago Manual of Style (16th Edition):

Farr, Michaela. “Bifidelity Methods for Polynomial Chaos Expansions.” 2017. Masters Thesis, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/mcen_gradetds/144.

MLA Handbook (7th Edition):

Farr, Michaela. “Bifidelity Methods for Polynomial Chaos Expansions.” 2017. Web. 01 Mar 2021.

Vancouver:

Farr M. Bifidelity Methods for Polynomial Chaos Expansions. [Internet] [Masters thesis]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/mcen_gradetds/144.

Council of Science Editors:

Farr M. Bifidelity Methods for Polynomial Chaos Expansions. [Masters Thesis]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/mcen_gradetds/144


University of Colorado

9. Eckert, Nathan James. Review of Railgun Modeling Techniques: Computation of Railgun Force and Other Key Factors.

Degree: MS, Aerospace Engineering Sciences, 2017, University of Colorado

  Currently, railgun force modeling either uses the simple “railgun force equation” or finite element methods. It is proposed here that a middle ground exists… (more)

Subjects/Keywords: current distribution; electromagnetic; inductance gradient; lorentz force; magnetic field; railgun; Aerospace Engineering; Models and Methods

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APA (6th Edition):

Eckert, N. J. (2017). Review of Railgun Modeling Techniques: Computation of Railgun Force and Other Key Factors. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/183

Chicago Manual of Style (16th Edition):

Eckert, Nathan James. “Review of Railgun Modeling Techniques: Computation of Railgun Force and Other Key Factors.” 2017. Masters Thesis, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/183.

MLA Handbook (7th Edition):

Eckert, Nathan James. “Review of Railgun Modeling Techniques: Computation of Railgun Force and Other Key Factors.” 2017. Web. 01 Mar 2021.

Vancouver:

Eckert NJ. Review of Railgun Modeling Techniques: Computation of Railgun Force and Other Key Factors. [Internet] [Masters thesis]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/183.

Council of Science Editors:

Eckert NJ. Review of Railgun Modeling Techniques: Computation of Railgun Force and Other Key Factors. [Masters Thesis]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/asen_gradetds/183


University of Colorado

10. Trowbridge, Michael Aaron. Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors.

Degree: MS, Aerospace Engineering Sciences, 2014, University of Colorado

  A software prototype for autonomous 3D scanning of uncooperatively rotating orbital debris using a point cloud sensor is designed and tested. The software successfully… (more)

Subjects/Keywords: 3D scanning; explicit loop closure heuristic; Graph SLAM; model generation; orbital debris; point clouds; Aerospace Engineering; Artificial Intelligence and Robotics; Computer-Aided Engineering and Design; Systems Engineering and Multidisciplinary Design Optimization

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APA (6th Edition):

Trowbridge, M. A. (2014). Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/86

Chicago Manual of Style (16th Edition):

Trowbridge, Michael Aaron. “Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors.” 2014. Masters Thesis, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/86.

MLA Handbook (7th Edition):

Trowbridge, Michael Aaron. “Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors.” 2014. Web. 01 Mar 2021.

Vancouver:

Trowbridge MA. Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors. [Internet] [Masters thesis]. University of Colorado; 2014. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/86.

Council of Science Editors:

Trowbridge MA. Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors. [Masters Thesis]. University of Colorado; 2014. Available from: https://scholar.colorado.edu/asen_gradetds/86


University of Colorado

11. Benzaken, Joseph David. Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis.

Degree: PhD, 2018, University of Colorado

 In this dissertation, we present a methodology for understanding the propagation and control of geometric variation in engineering design and analysis. This work is comprised… (more)

Subjects/Keywords: design space exploration; manifold optimization; parametric partial differential equations; thin shell structures; tolerance allocation protocols; uncertainty quantification; Aerospace Engineering; Applied Mathematics

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APA (6th Edition):

Benzaken, J. D. (2018). Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/108

Chicago Manual of Style (16th Edition):

Benzaken, Joseph David. “Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis.” 2018. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/appm_gradetds/108.

MLA Handbook (7th Edition):

Benzaken, Joseph David. “Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis.” 2018. Web. 01 Mar 2021.

Vancouver:

Benzaken JD. Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis. [Internet] [Doctoral dissertation]. University of Colorado; 2018. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/appm_gradetds/108.

Council of Science Editors:

Benzaken JD. Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis. [Doctoral Dissertation]. University of Colorado; 2018. Available from: https://scholar.colorado.edu/appm_gradetds/108


University of Colorado

12. Fairbanks, Hillary Ruth. Low-Rank, Multi-Fidelity Methods for Uncertainty Quantification of High-Dimensional Systems.

Degree: PhD, 2018, University of Colorado

  Characterizing and incorporating uncertainties when simulating physical phenomena is essential for improving model-based predictions. These uncertainties may stem from a lack of knowledge regarding… (more)

Subjects/Keywords: bi-fidelity approximations; low-rank approximations; multi-fidelity approximations; parametric model reduction; uncertainty quantification; Applied Mathematics; Models and Methods

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APA (6th Edition):

Fairbanks, H. R. (2018). Low-Rank, Multi-Fidelity Methods for Uncertainty Quantification of High-Dimensional Systems. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/114

Chicago Manual of Style (16th Edition):

Fairbanks, Hillary Ruth. “Low-Rank, Multi-Fidelity Methods for Uncertainty Quantification of High-Dimensional Systems.” 2018. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/appm_gradetds/114.

MLA Handbook (7th Edition):

Fairbanks, Hillary Ruth. “Low-Rank, Multi-Fidelity Methods for Uncertainty Quantification of High-Dimensional Systems.” 2018. Web. 01 Mar 2021.

Vancouver:

Fairbanks HR. Low-Rank, Multi-Fidelity Methods for Uncertainty Quantification of High-Dimensional Systems. [Internet] [Doctoral dissertation]. University of Colorado; 2018. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/appm_gradetds/114.

Council of Science Editors:

Fairbanks HR. Low-Rank, Multi-Fidelity Methods for Uncertainty Quantification of High-Dimensional Systems. [Doctoral Dissertation]. University of Colorado; 2018. Available from: https://scholar.colorado.edu/appm_gradetds/114


University of Colorado

13. Hsieh, Alan Sean-Ker. Direct Numerical Simulation of Complex Turbulence.

Degree: PhD, 2017, University of Colorado

  Direct numerical simulations (DNS) of spanwise-rotating turbulent channel flow were conducted. The data base obtained from these DNS simulations were used to investigate the… (more)

Subjects/Keywords: direct numerical simulation; modeling; rotating channel flow; turbulence; principal orthogonal decomposition; Aerospace Engineering; Applied Mathematics

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APA (6th Edition):

Hsieh, A. S. (2017). Direct Numerical Simulation of Complex Turbulence. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/234

Chicago Manual of Style (16th Edition):

Hsieh, Alan Sean-Ker. “Direct Numerical Simulation of Complex Turbulence.” 2017. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/234.

MLA Handbook (7th Edition):

Hsieh, Alan Sean-Ker. “Direct Numerical Simulation of Complex Turbulence.” 2017. Web. 01 Mar 2021.

Vancouver:

Hsieh AS. Direct Numerical Simulation of Complex Turbulence. [Internet] [Doctoral dissertation]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/234.

Council of Science Editors:

Hsieh AS. Direct Numerical Simulation of Complex Turbulence. [Doctoral Dissertation]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/asen_gradetds/234


University of Colorado

14. Qi, Hanchao. Low-Dimensional Signal Models in Compressive Sensing.

Degree: PhD, Electrical, Computer & Energy Engineering, 2013, University of Colorado

  In today's world, we often face an explosion of data that can be difficult to handle. Signal models help make this data tractable, and… (more)

Subjects/Keywords: algorithms; compressive sensing; nonlinear manifolds; high-dimensional signals; Electrical and Computer Engineering

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APA (6th Edition):

Qi, H. (2013). Low-Dimensional Signal Models in Compressive Sensing. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/ecen_gradetds/68

Chicago Manual of Style (16th Edition):

Qi, Hanchao. “Low-Dimensional Signal Models in Compressive Sensing.” 2013. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/ecen_gradetds/68.

MLA Handbook (7th Edition):

Qi, Hanchao. “Low-Dimensional Signal Models in Compressive Sensing.” 2013. Web. 01 Mar 2021.

Vancouver:

Qi H. Low-Dimensional Signal Models in Compressive Sensing. [Internet] [Doctoral dissertation]. University of Colorado; 2013. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/ecen_gradetds/68.

Council of Science Editors:

Qi H. Low-Dimensional Signal Models in Compressive Sensing. [Doctoral Dissertation]. University of Colorado; 2013. Available from: https://scholar.colorado.edu/ecen_gradetds/68


University of Colorado

15. Pourkamali Anaraki, Farhad. Randomized Algorithms for Large-Scale Data Analysis.

Degree: PhD, 2017, University of Colorado

  Massive high-dimensional data sets are ubiquitous in all scientific disciplines. Extracting meaningful information from these data sets will bring future advances in fields of… (more)

Subjects/Keywords: massive data sets; data storage; high-dimensional data sets; Applied Mathematics; Computer Sciences; Electrical and Computer Engineering

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APA (6th Edition):

Pourkamali Anaraki, F. (2017). Randomized Algorithms for Large-Scale Data Analysis. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/ecen_gradetds/141

Chicago Manual of Style (16th Edition):

Pourkamali Anaraki, Farhad. “Randomized Algorithms for Large-Scale Data Analysis.” 2017. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/ecen_gradetds/141.

MLA Handbook (7th Edition):

Pourkamali Anaraki, Farhad. “Randomized Algorithms for Large-Scale Data Analysis.” 2017. Web. 01 Mar 2021.

Vancouver:

Pourkamali Anaraki F. Randomized Algorithms for Large-Scale Data Analysis. [Internet] [Doctoral dissertation]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/ecen_gradetds/141.

Council of Science Editors:

Pourkamali Anaraki F. Randomized Algorithms for Large-Scale Data Analysis. [Doctoral Dissertation]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/ecen_gradetds/141


University of Colorado

16. Benzaken, Joseph D. Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis.

Degree: PhD, Applied Mathematics, 2018, University of Colorado

  In this dissertation, we present a methodology for understanding the propagation and control of geometric variation in engineering design and analysis. This work is… (more)

Subjects/Keywords: Design Space Exploration; Manifold Optimization; Parametric Partial Differential Equations; Thin Shell Structures; Tolerance Allocation Protocols; Uncertainty Quantification; Numerical Analysis and Computation; Partial Differential Equations; Structures and Materials

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APA (6th Edition):

Benzaken, J. D. (2018). Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/137

Chicago Manual of Style (16th Edition):

Benzaken, Joseph D. “Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis.” 2018. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/appm_gradetds/137.

MLA Handbook (7th Edition):

Benzaken, Joseph D. “Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis.” 2018. Web. 01 Mar 2021.

Vancouver:

Benzaken JD. Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis. [Internet] [Doctoral dissertation]. University of Colorado; 2018. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/appm_gradetds/137.

Council of Science Editors:

Benzaken JD. Propagation and Control of Geometric Variation in Engineering Structural Design and Analysis. [Doctoral Dissertation]. University of Colorado; 2018. Available from: https://scholar.colorado.edu/appm_gradetds/137


University of Colorado

17. Mindock, Jennifer. Development and Application of Spaceflight Performance Shaping Factors for Human Reliability Analysis.

Degree: PhD, Aerospace Engineering Sciences, 2012, University of Colorado

  The ability of crewmembers to perform various critical functions during spacecraft operations is widely recognized as being essential to mission success. This necessity motivates… (more)

Subjects/Keywords: Analytic Hierarchy Process; Bayesian Network; Human Reliability Analysis; Performance Influencing Factors; Performance Shaping Factors; Spaceflight; Aerospace Engineering; Engineering

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APA (6th Edition):

Mindock, J. (2012). Development and Application of Spaceflight Performance Shaping Factors for Human Reliability Analysis. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/47

Chicago Manual of Style (16th Edition):

Mindock, Jennifer. “Development and Application of Spaceflight Performance Shaping Factors for Human Reliability Analysis.” 2012. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/47.

MLA Handbook (7th Edition):

Mindock, Jennifer. “Development and Application of Spaceflight Performance Shaping Factors for Human Reliability Analysis.” 2012. Web. 01 Mar 2021.

Vancouver:

Mindock J. Development and Application of Spaceflight Performance Shaping Factors for Human Reliability Analysis. [Internet] [Doctoral dissertation]. University of Colorado; 2012. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/47.

Council of Science Editors:

Mindock J. Development and Application of Spaceflight Performance Shaping Factors for Human Reliability Analysis. [Doctoral Dissertation]. University of Colorado; 2012. Available from: https://scholar.colorado.edu/asen_gradetds/47


University of Colorado

18. Biagioni, David Joseph. Numerical construction of Green’s functions in high dimensional elliptic problems with variable coefficients and analysis of renewable energy data via sparse and separable approximations.

Degree: PhD, Applied Mathematics, 2012, University of Colorado

  This thesis consists of two parts. In Part I, we describe an algorithm for approximating the Green's function for elliptic problems with variable coefficients… (more)

Subjects/Keywords: Curse of dimensionality; Direct Poisson solver; High dimensional partial differential equations; Numerical analysis; Randomized canonical tensor decomposition; Separated representations; Applied Mathematics

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APA (6th Edition):

Biagioni, D. J. (2012). Numerical construction of Green’s functions in high dimensional elliptic problems with variable coefficients and analysis of renewable energy data via sparse and separable approximations. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/29

Chicago Manual of Style (16th Edition):

Biagioni, David Joseph. “Numerical construction of Green’s functions in high dimensional elliptic problems with variable coefficients and analysis of renewable energy data via sparse and separable approximations.” 2012. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/appm_gradetds/29.

MLA Handbook (7th Edition):

Biagioni, David Joseph. “Numerical construction of Green’s functions in high dimensional elliptic problems with variable coefficients and analysis of renewable energy data via sparse and separable approximations.” 2012. Web. 01 Mar 2021.

Vancouver:

Biagioni DJ. Numerical construction of Green’s functions in high dimensional elliptic problems with variable coefficients and analysis of renewable energy data via sparse and separable approximations. [Internet] [Doctoral dissertation]. University of Colorado; 2012. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/appm_gradetds/29.

Council of Science Editors:

Biagioni DJ. Numerical construction of Green’s functions in high dimensional elliptic problems with variable coefficients and analysis of renewable energy data via sparse and separable approximations. [Doctoral Dissertation]. University of Colorado; 2012. Available from: https://scholar.colorado.edu/appm_gradetds/29


University of Colorado

19. Chitale, Kedar C. Anisotropic Mesh Adaptivity for Turbulent Flows with Boundary Layers.

Degree: PhD, Aerospace Engineering Sciences, 2013, University of Colorado

  Turbulent flows are found everywhere in nature and are studied, analyzed and simulated using various experimental and numerical tools. For computational analysis, a variety… (more)

Subjects/Keywords: Adaptive mesh generation; Anisotropic adaptivity; Boundary layers; Computational fluid dynamics; Multi element wings; Turbulent flows; Aerospace Engineering

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APA (6th Edition):

Chitale, K. C. (2013). Anisotropic Mesh Adaptivity for Turbulent Flows with Boundary Layers. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/68

Chicago Manual of Style (16th Edition):

Chitale, Kedar C. “Anisotropic Mesh Adaptivity for Turbulent Flows with Boundary Layers.” 2013. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/68.

MLA Handbook (7th Edition):

Chitale, Kedar C. “Anisotropic Mesh Adaptivity for Turbulent Flows with Boundary Layers.” 2013. Web. 01 Mar 2021.

Vancouver:

Chitale KC. Anisotropic Mesh Adaptivity for Turbulent Flows with Boundary Layers. [Internet] [Doctoral dissertation]. University of Colorado; 2013. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/68.

Council of Science Editors:

Chitale KC. Anisotropic Mesh Adaptivity for Turbulent Flows with Boundary Layers. [Doctoral Dissertation]. University of Colorado; 2013. Available from: https://scholar.colorado.edu/asen_gradetds/68


University of Colorado

20. Golmon, Stephanie L. Multi-Scale Simulation and Optimization of Lithium Battery Performance.

Degree: PhD, Aerospace Engineering Sciences, 2014, University of Colorado

  The performance and degradation of lithium batteries strongly depends on electrochemical, mechanical, and thermal phenomena. While a large volume of work has focused on… (more)

Subjects/Keywords: design optimization; electrodes; Li-ion batteries; multi-scale modeling; particle size; porosity; Aerospace Engineering; Power and Energy; Transport Phenomena

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APA (6th Edition):

Golmon, S. L. (2014). Multi-Scale Simulation and Optimization of Lithium Battery Performance. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/80

Chicago Manual of Style (16th Edition):

Golmon, Stephanie L. “Multi-Scale Simulation and Optimization of Lithium Battery Performance.” 2014. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/80.

MLA Handbook (7th Edition):

Golmon, Stephanie L. “Multi-Scale Simulation and Optimization of Lithium Battery Performance.” 2014. Web. 01 Mar 2021.

Vancouver:

Golmon SL. Multi-Scale Simulation and Optimization of Lithium Battery Performance. [Internet] [Doctoral dissertation]. University of Colorado; 2014. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/80.

Council of Science Editors:

Golmon SL. Multi-Scale Simulation and Optimization of Lithium Battery Performance. [Doctoral Dissertation]. University of Colorado; 2014. Available from: https://scholar.colorado.edu/asen_gradetds/80


University of Colorado

21. Feldhacker, Juliana D. Incorporating Uncertainty into Spacecraft Mission and Trajectory Design.

Degree: PhD, Aerospace Engineering Sciences, 2016, University of Colorado

  The complex nature of many astrodynamic systems often leads to high computational costs or degraded accuracy in the analysis and design of spacecraft missions,… (more)

Subjects/Keywords: mission design; optimization under uncertainty; robust design; trajectory optimization; uncertainty quantification; Aerospace Engineering

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APA (6th Edition):

Feldhacker, J. D. (2016). Incorporating Uncertainty into Spacecraft Mission and Trajectory Design. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/135

Chicago Manual of Style (16th Edition):

Feldhacker, Juliana D. “Incorporating Uncertainty into Spacecraft Mission and Trajectory Design.” 2016. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/135.

MLA Handbook (7th Edition):

Feldhacker, Juliana D. “Incorporating Uncertainty into Spacecraft Mission and Trajectory Design.” 2016. Web. 01 Mar 2021.

Vancouver:

Feldhacker JD. Incorporating Uncertainty into Spacecraft Mission and Trajectory Design. [Internet] [Doctoral dissertation]. University of Colorado; 2016. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/135.

Council of Science Editors:

Feldhacker JD. Incorporating Uncertainty into Spacecraft Mission and Trajectory Design. [Doctoral Dissertation]. University of Colorado; 2016. Available from: https://scholar.colorado.edu/asen_gradetds/135


University of Colorado

22. Hadigol, Mohammad. Uncertainty Quantification of Coupled Problems with Applications to Lithium-ion Batteries.

Degree: PhD, Aerospace Engineering Sciences, 2016, University of Colorado

  This thesis includes three main parts that are concerned with the propagation of uncertainty across high-dimensional coupled problems with applications to Lithium-ion batteries (LIBs).… (more)

Subjects/Keywords: Coupled Domain; High-dimensional; Lithium-ion Battery; Optimal Sampling; Polynomial Chaos Expansion; Uncertainty Quantification; Applied Mathematics; Engineering; Power and Energy

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APA (6th Edition):

Hadigol, M. (2016). Uncertainty Quantification of Coupled Problems with Applications to Lithium-ion Batteries. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/137

Chicago Manual of Style (16th Edition):

Hadigol, Mohammad. “Uncertainty Quantification of Coupled Problems with Applications to Lithium-ion Batteries.” 2016. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/137.

MLA Handbook (7th Edition):

Hadigol, Mohammad. “Uncertainty Quantification of Coupled Problems with Applications to Lithium-ion Batteries.” 2016. Web. 01 Mar 2021.

Vancouver:

Hadigol M. Uncertainty Quantification of Coupled Problems with Applications to Lithium-ion Batteries. [Internet] [Doctoral dissertation]. University of Colorado; 2016. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/137.

Council of Science Editors:

Hadigol M. Uncertainty Quantification of Coupled Problems with Applications to Lithium-ion Batteries. [Doctoral Dissertation]. University of Colorado; 2016. Available from: https://scholar.colorado.edu/asen_gradetds/137


University of Colorado

23. Jenkins, Nicholas J. Immersed Boundary Methods for Optimization of Strongly Coupled Fluid-Structure Systems.

Degree: PhD, Aerospace Engineering Sciences, 2017, University of Colorado

  Conventional methods for design of tightly coupled multidisciplinary systems, such as fluid-structure interaction (FSI) problems, traditionally rely on manual revisions informed by a loosely… (more)

Subjects/Keywords: computational fluid dynamics; extended finite element method; fluid-structure interaction; immersed boundary; level set method; topology optimization; Aerospace Engineering; Mechanical Engineering; Systems Engineering and Multidisciplinary Design Optimization

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APA (6th Edition):

Jenkins, N. J. (2017). Immersed Boundary Methods for Optimization of Strongly Coupled Fluid-Structure Systems. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/140

Chicago Manual of Style (16th Edition):

Jenkins, Nicholas J. “Immersed Boundary Methods for Optimization of Strongly Coupled Fluid-Structure Systems.” 2017. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/140.

MLA Handbook (7th Edition):

Jenkins, Nicholas J. “Immersed Boundary Methods for Optimization of Strongly Coupled Fluid-Structure Systems.” 2017. Web. 01 Mar 2021.

Vancouver:

Jenkins NJ. Immersed Boundary Methods for Optimization of Strongly Coupled Fluid-Structure Systems. [Internet] [Doctoral dissertation]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/140.

Council of Science Editors:

Jenkins NJ. Immersed Boundary Methods for Optimization of Strongly Coupled Fluid-Structure Systems. [Doctoral Dissertation]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/asen_gradetds/140


University of Colorado

24. Villanueva Pérez, Carlos Hernán. Topology Optimization Using the Level Set and eXtended Finite Element Methods: Theory and Applications.

Degree: PhD, Mechanical Engineering, 2016, University of Colorado

 Computational design optimization provides designers with automated techniques to develop novel and non-intuitive optimal designs. Topology optimization is a design optimization technique that allows for… (more)

Subjects/Keywords: eXtended Finite Element Method; Face-oriented Ghost-penalty Methods; Laminar Incompressible Flow; Level Set Method; Topology Optimization; Weak Boundary Conditions; Aerospace Engineering; Mechanical Engineering

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APA (6th Edition):

Villanueva Pérez, C. H. (2016). Topology Optimization Using the Level Set and eXtended Finite Element Methods: Theory and Applications. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/mcen_gradetds/123

Chicago Manual of Style (16th Edition):

Villanueva Pérez, Carlos Hernán. “Topology Optimization Using the Level Set and eXtended Finite Element Methods: Theory and Applications.” 2016. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/mcen_gradetds/123.

MLA Handbook (7th Edition):

Villanueva Pérez, Carlos Hernán. “Topology Optimization Using the Level Set and eXtended Finite Element Methods: Theory and Applications.” 2016. Web. 01 Mar 2021.

Vancouver:

Villanueva Pérez CH. Topology Optimization Using the Level Set and eXtended Finite Element Methods: Theory and Applications. [Internet] [Doctoral dissertation]. University of Colorado; 2016. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/mcen_gradetds/123.

Council of Science Editors:

Villanueva Pérez CH. Topology Optimization Using the Level Set and eXtended Finite Element Methods: Theory and Applications. [Doctoral Dissertation]. University of Colorado; 2016. Available from: https://scholar.colorado.edu/mcen_gradetds/123


University of Colorado

25. Walter, Sibylle F. Optimization of Pressure Probe Placement and Data Analysis of Engine-Inlet Distortion.

Degree: PhD, Aerospace Engineering Sciences, 2016, University of Colorado

  The purpose of this research is to examine methods by which quantification of inlet flow distortion may be improved upon. Specifically, this research investigates… (more)

Subjects/Keywords: Inlet flow distortion; Propulsion integration; Supersonic inlet design; Aerodynamics and Fluid Mechanics; Aerospace Engineering

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APA (6th Edition):

Walter, S. F. (2016). Optimization of Pressure Probe Placement and Data Analysis of Engine-Inlet Distortion. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/154

Chicago Manual of Style (16th Edition):

Walter, Sibylle F. “Optimization of Pressure Probe Placement and Data Analysis of Engine-Inlet Distortion.” 2016. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/154.

MLA Handbook (7th Edition):

Walter, Sibylle F. “Optimization of Pressure Probe Placement and Data Analysis of Engine-Inlet Distortion.” 2016. Web. 01 Mar 2021.

Vancouver:

Walter SF. Optimization of Pressure Probe Placement and Data Analysis of Engine-Inlet Distortion. [Internet] [Doctoral dissertation]. University of Colorado; 2016. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/154.

Council of Science Editors:

Walter SF. Optimization of Pressure Probe Placement and Data Analysis of Engine-Inlet Distortion. [Doctoral Dissertation]. University of Colorado; 2016. Available from: https://scholar.colorado.edu/asen_gradetds/154


University of Colorado

26. Satkauskas, Ignas V. Numerical Calculus of Probability Density Functions.

Degree: PhD, Applied Mathematics, 2017, University of Colorado

  In this thesis we construct novel functional representations for the Probability Density Functions (PDFs) of random variables and develop efficient and accurate algorithms for… (more)

Subjects/Keywords: multiresolution analysis; probability density function; product of random variables; Applied Mathematics; Probability

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APA (6th Edition):

Satkauskas, I. V. (2017). Numerical Calculus of Probability Density Functions. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/93

Chicago Manual of Style (16th Edition):

Satkauskas, Ignas V. “Numerical Calculus of Probability Density Functions.” 2017. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/appm_gradetds/93.

MLA Handbook (7th Edition):

Satkauskas, Ignas V. “Numerical Calculus of Probability Density Functions.” 2017. Web. 01 Mar 2021.

Vancouver:

Satkauskas IV. Numerical Calculus of Probability Density Functions. [Internet] [Doctoral dissertation]. University of Colorado; 2017. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/appm_gradetds/93.

Council of Science Editors:

Satkauskas IV. Numerical Calculus of Probability Density Functions. [Doctoral Dissertation]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/appm_gradetds/93


University of Colorado

27. Lawry, Matthew W. A Topology Optimization Method for Structural Designs Reliant on Contact Phenomena.

Degree: PhD, 2016, University of Colorado

 This thesis introduces a comprehensive computational methodology for the topology optimization of contact problems, which is relevant to a broad range of engineering applications. The… (more)

Subjects/Keywords: computational contact mechanics; level set methods; structural optimization; topology optimization; XFEM; Aerospace Engineering; Mechanical Engineering

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APA (6th Edition):

Lawry, M. W. (2016). A Topology Optimization Method for Structural Designs Reliant on Contact Phenomena. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/186

Chicago Manual of Style (16th Edition):

Lawry, Matthew W. “A Topology Optimization Method for Structural Designs Reliant on Contact Phenomena.” 2016. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/186.

MLA Handbook (7th Edition):

Lawry, Matthew W. “A Topology Optimization Method for Structural Designs Reliant on Contact Phenomena.” 2016. Web. 01 Mar 2021.

Vancouver:

Lawry MW. A Topology Optimization Method for Structural Designs Reliant on Contact Phenomena. [Internet] [Doctoral dissertation]. University of Colorado; 2016. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/186.

Council of Science Editors:

Lawry MW. A Topology Optimization Method for Structural Designs Reliant on Contact Phenomena. [Doctoral Dissertation]. University of Colorado; 2016. Available from: https://scholar.colorado.edu/asen_gradetds/186


University of Colorado

28. Kabiri, Mirmohammadreza. Adaptive Concurrent Multiscale Method for Fracture of Material and Size Effect Problem.

Degree: PhD, 2014, University of Colorado

 An adaptive concurrent multiscale methodology (ACM2) is introduced to enable strong interaction between both macroscopic and microscopic deformation fields. The method is formulated in finite… (more)

Subjects/Keywords: macroscopic crack; heterogeneous media; crack propagation; computation; Civil Engineering

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APA (6th Edition):

Kabiri, M. (2014). Adaptive Concurrent Multiscale Method for Fracture of Material and Size Effect Problem. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/cven_gradetds/113

Chicago Manual of Style (16th Edition):

Kabiri, Mirmohammadreza. “Adaptive Concurrent Multiscale Method for Fracture of Material and Size Effect Problem.” 2014. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/cven_gradetds/113.

MLA Handbook (7th Edition):

Kabiri, Mirmohammadreza. “Adaptive Concurrent Multiscale Method for Fracture of Material and Size Effect Problem.” 2014. Web. 01 Mar 2021.

Vancouver:

Kabiri M. Adaptive Concurrent Multiscale Method for Fracture of Material and Size Effect Problem. [Internet] [Doctoral dissertation]. University of Colorado; 2014. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/cven_gradetds/113.

Council of Science Editors:

Kabiri M. Adaptive Concurrent Multiscale Method for Fracture of Material and Size Effect Problem. [Doctoral Dissertation]. University of Colorado; 2014. Available from: https://scholar.colorado.edu/cven_gradetds/113


University of Colorado

29. Lang, Christapher. An XFEM Approach to Modeling Material Interface Uncertainty.

Degree: PhD, Aerospace Engineering Sciences, 2015, University of Colorado

  The focus of this research is uncertainty modeling for problems with random geometry. This dissertation develops a computational framework, based on the eXtended Finite… (more)

Subjects/Keywords: Level Set Method; Polynomial Chaos; Uncertainty Analysis; XFEM; X-SFEM; Structures and Materials

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APA (6th Edition):

Lang, C. (2015). An XFEM Approach to Modeling Material Interface Uncertainty. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/111

Chicago Manual of Style (16th Edition):

Lang, Christapher. “An XFEM Approach to Modeling Material Interface Uncertainty.” 2015. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/asen_gradetds/111.

MLA Handbook (7th Edition):

Lang, Christapher. “An XFEM Approach to Modeling Material Interface Uncertainty.” 2015. Web. 01 Mar 2021.

Vancouver:

Lang C. An XFEM Approach to Modeling Material Interface Uncertainty. [Internet] [Doctoral dissertation]. University of Colorado; 2015. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/asen_gradetds/111.

Council of Science Editors:

Lang C. An XFEM Approach to Modeling Material Interface Uncertainty. [Doctoral Dissertation]. University of Colorado; 2015. Available from: https://scholar.colorado.edu/asen_gradetds/111


University of Colorado

30. Peng, Ji. Uncertainty Quantification via Sparse Polynomial Chaos Expansion.

Degree: PhD, Mechanical Engineering, 2015, University of Colorado

  Uncertainty quantification (UQ) is an emerging research area that aims to develop methods for accurate predictions of quantities of interest (QoI's) from complex engineering… (more)

Subjects/Keywords: Basis design; Compressive sampling; Polynomial chaos expansion; Sparse approximation; Uncertainty quantification; Applied Mathematics; Mechanical Engineering; Statistics and Probability

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APA (6th Edition):

Peng, J. (2015). Uncertainty Quantification via Sparse Polynomial Chaos Expansion. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/mcen_gradetds/112

Chicago Manual of Style (16th Edition):

Peng, Ji. “Uncertainty Quantification via Sparse Polynomial Chaos Expansion.” 2015. Doctoral Dissertation, University of Colorado. Accessed March 01, 2021. https://scholar.colorado.edu/mcen_gradetds/112.

MLA Handbook (7th Edition):

Peng, Ji. “Uncertainty Quantification via Sparse Polynomial Chaos Expansion.” 2015. Web. 01 Mar 2021.

Vancouver:

Peng J. Uncertainty Quantification via Sparse Polynomial Chaos Expansion. [Internet] [Doctoral dissertation]. University of Colorado; 2015. [cited 2021 Mar 01]. Available from: https://scholar.colorado.edu/mcen_gradetds/112.

Council of Science Editors:

Peng J. Uncertainty Quantification via Sparse Polynomial Chaos Expansion. [Doctoral Dissertation]. University of Colorado; 2015. Available from: https://scholar.colorado.edu/mcen_gradetds/112

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